Reasoning traces map the step-by-step thought process behind an AI’s answer, showing how it arrives at conclusions. Developers use them to debug model logic, while researchers analyze these traces to improve transparency and accuracy. Data scientists benefit by auditing decisions, and end users gain trust through clear, explainable AI outcomes.
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